Pieter De Clercq

This study uses EEG to identify altered brain network patterns in chronic aphasia during natural speech listening, finding distinct connectivity differences and potential biomarkers.

This study investigates neural tracking of acoustic and linguistic speech representations in individuals with post-stroke aphasia and finds decreased neural tracking of acoustic speech properties compared to healthy controls.

This study uses EEG and deep learning to classify native versus foreign speech perception based on linguistic features and observes differences in neural tracking patterns.

This study investigates neural envelope tracking in post-stroke aphasia, finding that lesions in language areas like the middle temporal gyrus are associated with poorer tracking, and that tracking relates to auditory and language skills.

This study investigates whether the multiple demand network is involved in language processing in chronic post-stroke aphasia using individualized functional localization.

This paper compares linear and mutual information analyses of EEG data to study neural envelope tracking, finding that mutual information, particularly using Gaussian copula, better captures nonlinear speech processing.

This study shows individuals with aphasia have impaired acoustic and phonemic processing, with 76% showing low-level impairments that predict higher-level language processing difficulties.